How Can Python\'s `timeit` Module Help Compare the Performance of Different Sorting Algorithms?

Comparing Function Performance with the timeit Module

The timeit module provides a versatile tool for measuring the execution times of Python functions. To compare the performance of your own functions, such as "insertion_sort" and "tim_sort", follow these steps:

Interactive Python Session (IPython Shell):

1. Use the %timeit special function for convenient timing. For example:

In [1]: def insertion_sort(array):
   ...:     # your code for insertion sort
   ...:

In [2]: %timeit for _ in range(100): insertion_sort(array)
1000 loops, best of 3: 25.6 us per loop

2. Import functions and names from __main__ for use in the standard Python interpreter:

>>> import timeit
>>> timeit.repeat("for _ in range(100): tim_sort(array)", "from __main__ import tim_sort",
                  number=100000)
[2.0640320777893066, 2.0876040458679199, 2.0520210266113281]

By comparing these results, you can assess the relative speed of your "insertion_sort" and "tim_sort" functions and optimize them accordingly.

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